WeChat Mini Program
Old Version Features

Features of Using the Lithogeochemical Indicators for the Reconstruction of Paleoclimate and Composition of Demolition Sources in the Late Jurassic-Lower Cretaceous West Siberian Sedimentary Basin

V. G. Eder, A. G. Zamiralova,P. A. Yan

Литология и полезные ископаемые(2023)

Geological Institute of the Russian Academy of Sciences

Cited 0|Views5
Abstract
For the rocks of the Upper Jurassic-Lower Cretaceous Bazhenov formation, a significant positive linear dependence of the Th, Hf, Sc, La content on the Al2O3 content was revealed, and their terrigenous genesis was confirmed. It has been determined that the samples in which the distribution of the values of the Sc/Al2O3 and La/Al2O3 ratios does not satisfy the linear dependence are mixed clayey-siliceous rocks with a P2O5 content 1 mas. % or substantially pyritized (in which the content of pyrite exceeds the content of S and C/S ≤ 1), as well as siliceous mudstones with a SiO2 content 70 mas. % by weight. It is concluded that before analyzing geochemical indicators for reconstructing the conditions of formation of the Bazhenov formation, in addition to carbonated rocks, rocks of the above types, as well as rocks that have undergone late diagenetic kaolinization, should be excluded from the analysis. The conditions of formation of the studied deposits were reconstructed based on the analysis of the values of a number of geochemical modules and indicators. As a result of the study of CIA, CIW variations, it was confirmed that the climate in the Late Jurassic-Early Cretaceous period in the West Siberian sedimentary basin was warm, semiarid. It was revealed that during the entire period under review, it did not change significantly. For the deposits of the Bazhenov formation, a number of indicators such as (La/Yb)N, Eu/Eu*, as well as the distribution of trace element content values on the triangular diagram Th‒La‒Sc, suggest that in the central and southeastern regions of the formation distribution area, the sources of demolition of the mafic composition prevailed.
More
Translated text
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined